In the field of image capture and reproduction, processing parameters of the image capture and image display devices are pre-set by the manufacturers. Typically, the manufacturers adjust these parameters so that the created image looks “good” so that the user will be satisfied with the result. This is referred to as the “photofinishing or preferred reproduction model” as opposed to the “colorimetric reproduction model” which seeks to convey the correct colors of a subject. For example, many digital cameras perform an operation called “white balancing” that adjusts the imaging parameters so that the overall average color of an image is, for example, that of a half-brightness gray image (50% gray). This assumes that the view imaged is in fact 50% gray, which is rarely true. Thus, white balancing is an arbitrary adjustment that works qualitatively to produce a viewable image, but not quantitatively to produce a correctly depicted image.
In an exemplary white balancing process, the darkest and lightest depicted values (e.g., black and white levels) in an image are usually clipped by an analysis of the distribution of brightness levels observed. The clipping is done to ensure good use of the available signal range. A pre-specified percentage of, for example, dark and light values are clipped and mapped to the same value (e.g., to zero or a maximum value). Values in between are then scaled through the available range. However, this scaling may distort the true color spectra in order to make the resulting image more appealing. These adjustments are usually pre-defined by the manufacturer and applied uniformly to all of the acquired images. Thus, the processing parameters of the digital camera do not address rendering the “true” color of the items in the view, since this cannot be determined without other information.
Additionally, the ambient lighting conditions present when an image is captured can distort the overall coloration of an image. For example, if a picture is taken indoors, the light radiated by lighting fixtures may be weighted in a particular range of the color spectrum. For example, fluorescent lighting emits light with a slightly bluish tint. Thus, a picture taken in the presence of fluorescent lighting will be distorted by the ambient light and will depict the subject with more blue tones than may actually be present.
To overcome these distortions, a controlled environment may be provided in which the image processing parameters of the image capture equipment is carefully calibrated and monitored. These controlled environments also rely upon carefully calibrated and controlled lighting so that any distortions generated by the ambient lighting and image processing equipment are either known, or minimized.
In addition to the problem of capturing an image that is photometrically correct, displaying the image without introducing distortion of the color space is also a problem. For example, the color reproduction of a computer monitor, or other display device, changes over time. As a result, there may be some “drift” of the displayed color values over time from the pre-set calibration parameters. In applications in which it is important that color rendering must remain consistent (e.g., computer animation) it is necessary to perform a detailed analysis and re-calibration of the computer monitors occasionally. Similarly, printers are calibrated before sale, but online calibration is usually limited to on/off testing of nozzle function. Scanners can be used to calibrate, or re-calibrate, colors, but these combine possible inaccuracies from both the printing and scanning of an image.